Radio map updated method based on subscriber locations in indoor WLAN localization

With the rapid development of wireless local area network （WLAN） technology, an important target of indoor positioning systems is to improve the positioning accuracy while reducing the online calibration effort to overcome signal time-varying. A novel fingerprint positioning algorithm, known as the adaptive radio map with updated method based on hidden Markov model （HMM）, is proposed. It is shown that by using a collection of user traces that can be cheaply obtained, the proposed algorithm can take advantage of these data to update the labeled calibration data to further improve the position estimation accuracy. This algorithm is a combination of machine learning, information gain theory and fingerprinting. By collecting data and testing the algorithm in a realistic indoor WLAN environment, the experiment results indicate that, compared with the widely used K nearest neighbor algorithm, the proposed algorithm can improve the positioning accuracy while greatly reduce the calibration effort.

A Semi-Supervised WLAN Indoor Localization Method Based on l1-Graph Algorithm

For indoor location estimation based on received signal strength( RSS) in wireless local area networks( WLAN),in order to reduce the influence of noise on the positioning accuracy,a large number of RSS should be collected in offline phase. Therefore,collecting training data with positioning information is time consuming which becomes the bottleneck of WLAN indoor localization. In this paper,the traditional semisupervised learning method based on k-NN and ε-NN graph for reducing collection workload of offline phase are analyzed,and the result shows that the k-NN or ε-NN graph are sensitive to data noise,which limit the performance of semi-supervised learning WLAN indoor localization system. Aiming at the above problem,it proposes a l1-graph-algorithm-based semi-supervised learning( LG-SSL) indoor localization method in which the graph is built by l1-norm algorithm. In our system,it firstly labels the unlabeled data using LG-SSL and labeled data to build the Radio Map in offline training phase,and then uses LG-SSL to estimate user's location in online phase. Extensive experimental results show that,benefit from the robustness to noise and sparsity ofl1-graph,LG-SSL exhibits superior performance by effectively reducing the collection workload in offline phase and improving localization accuracy in online phase.

A shock wave overpressure test system based on WLAN

Due to short transmission distance and low transmission speed when testing the shock wave overpressure with storage test method based on ZigBee technology, a new test method based on wireless local area network （WLAN） technology is proposed, which can monitor remote test nodes. Moreover, the wireless network is designed based on 802. 11b/g protocol, which is helpful for reading the data of the test nodes quickly. Therefore, the accessibility of distributed test system can be improved greatly. The field test results show that the test system performance is good and the transmission speed is high.

A KNN-based two-step fuzzy clustering weighted algorithm for WLAN indoor positioning

Although k-nearest neighbors （KNN） is a popular fingerprint match algorithm for its simplicity and accuracy, because it is sensitive to the circumstances, a fuzzy c-means （FCM） clustering algorithm is applied to improve it. Thus, a KNN-based two-step FCM weighted （KTFW） algorithm for indoor positioning in wireless local area networks （WLAN） is presented in this paper. In KTFW algorithm, k reference points （RPs） chosen by KNN are clustered through FCM based on received signal strength （RSS） and location coordinates. The right clusters are chosen according to rules, so three sets of RPs are formed including the set of k RPs chosen by KNN and are given different weights. RPs supposed to have better contribution to positioning accuracy are given larger weights to improve the positioning accuracy. Simulation results indicate that KTFW generally outperforms KNN and its complexity is greatly reduced through providing initial clustering centers for FCM.

Secure Authentication of WLAN Based on Elliptic Curve Cryptosystem

The security of wireless local area network （WI.AN） becomes a bottleneck for its further applications. At present, many standard organizations and manufacturers of WLAN try to solve this problem. However, owing to the serious secure leak in IEEES02.11 standards, it is impossible to utterly solve the problem by simply adding some remedies. Based on the analysis on the security mechanism of WLAN and the latest techniques of WI.AN security, a solution to WLAN security was presented. The solution makes preparation for the further combination of WLAN and Internet.

Security Analysis of Application Layer Protocols on Wireless Local Area Networks

This paper aims at analyzing the security issues that lie in the application layer (AL) protocols when users connect to the Internet via a wireless local area network (WLAN) through an access point. When adversaries launch deauthentication flood attacks cutting users' connection, the connection managers will automatically research the last access point's extended service set identifier (ESSID) and then re-establish connection. However, such re-connection can lead the users to a fake access point with the same ESSID set by attackers. As the attackers hide behind users' access points, they can pass AL's authentication and security schemes, e.g. secure socket layer (SSL). We have proved that they can even spy on users' account details, passwords, data and privacy.

A DELAY BASED BACKOFF SCHEME FOR WLAN WITH QoS GUARANTEE AND ITS PERFORMANCE

Based on the Distributed Coordination Function (DCF) and the Enhanced DCF (EDCF) mechanisms in IEEE 802.11 and 802.11e, a novel backoff scheme for Wireless Local Area Network (WLAN) is proposed. The scheme is to solve the problem of the packet loss and the decrease of performance due to the increasing Contention Window (CW) when there are continuous collisions. In the proposed scheme, the CW of the packet will change dynamically with different delay for the different traffics. Mathematic formulas are presented to indicate the relationship between the CW and the delay character. ,The performance of the new scheme is also discussed with simulation results. The results show that it helps WLAN system handle multimedia simultaneously.

A random adaptive method to adjust MAC parameters in IEEE802.11e WLAN

The IEEE 802.11e standard is proposed to provide QoS support in WLAN by providing prioritized differentiation of traffic. Since all the stations in the same priority access category (AC) have the same set of parameters, when the number of stations increases, the probability of different stations in the same AC choosing the same values will increase, which will result in collisions. Random adaptive MAC (medium access control) parameters scheme (RAMPS) is proposed, which uses random adaptive MAC differentiation parameters instead of the static ones used in the 802.11e standard. The performance of RAMPS is compared with that of enhanced distributed coordination access (EDCA) using NS2. The results show that RAMPS can reduce collision rate of the AC and improve the throughput by using adaptive random contention window size and inter-frame spacing values. RAMPS ensures that at any given time, several flows of the same priority have different MAC parameter values. By using the random offset for the inter-frame spacing value and the backoff time, RAMPS can provide intra-AC differentiation. The simulation results show that RAMPS outperforms EDCA in terms of both throughput and end-to-end delay irrespective of the traffic load.

Achieving Efficient Channel Utilization for Data Communications in IEEE 802.11 WLAN

In the IEEE g02. 11 protocol, the adoption of the exponential backoff technique leads to throughput performance strongly dependent on the initial contention window size and, most importantly, on the number of contending stations considered in the network. This paper proposes a simple but accurate method to dynamically estimate the number of contending stations in a wireless local area network （ WLAN ）. Based on estimation, all the mobile stations dynamically adjust the initial contention window in medium access control （ MAC ） layer to avoid collisions. The simulation results show that the proposed algorithm can achieve efficient channel utilization, higher system throughput, and better fairness performance.

Resource Exhaustion Attack Detection Scheme for WLAN Using Artificial Neural Network

IEEE 802.11 Wi-Fi networks are prone to many denial of service(DoS)attacks due to vulnerabilities at the media access control(MAC)layer of the 802.11 protocol.Due to the data transmission nature of the wireless local area network(WLAN)through radio waves,its communication is exposed to the possibility of being attacked by illegitimate users.Moreover,the security design of the wireless structure is vulnerable to versatile attacks.For example,the attacker can imitate genuine features,rendering classificationbased methods inaccurate in differentiating between real and false messages.Althoughmany security standards have been proposed over the last decades to overcome many wireless network attacks,effectively detecting such attacks is crucial in today’s real-world applications.This paper presents a novel resource exhaustion attack detection scheme(READS)to detect resource exhaustion attacks effectively.The proposed scheme can differentiate between the genuine and fake management frames in the early stages of the attack such that access points can effectively mitigate the consequences of the attack.The scheme is built through learning from clustered samples using artificial neural networks to identify the genuine and rogue resource exhaustion management frames effectively and efficiently in theWLAN.The proposed scheme consists of four modules whichmake it capable to alleviates the attack impact more effectively than the related work.The experimental results show the effectiveness of the proposed technique by gaining an 89.11%improvement compared to the existing works in terms of detection.

A NOVEL LINK ADAPTATION SCHEME TO ENHANCE PERFORMANCE OF IEEE 802.11G WIRELESS LAN

A novel link adaptation scheme using linear Auto Regressive （AR） model channel estimation algorithm to enhance the performance of auto rate selection mechanism in IEEE 802.11g is proposed. This scheme can overcome the low efficiency caused by time interval between the time when Received Signal Strength （RSS） is measured and the time when rate is selected. The best rate is selected based on data payload length, frame retry count and the estimated RSS, which is estimated from recorded RSSs. Simulation results show that the proposed scheme enhances mean throughput performance up to 7%, in saturation state, and up to 24% in finite load state compared with those non-estimation schemes, performance enhancements in average drop rate and average number of transmission attempts per data frame delivery also validate the effectiveness of the proposed schelne.

A novel QoS supported cooperative diversity algorithm for IEEE 802.11 WLAN

A new cooperative diversity algorithm with quality of service （QoS） awareness for wireless local area network （WLAN） is proposed. According to this protocol, cooperation is invoked only if a direct transmission cannot meet user-specific QoS requirements. If cooperation is implemented, partner choice depends on who can achieve the minimum data rate required to have a successful transmission. The closed-form expressions for the system throughput and the power consumption are provided. Theoretical analysis and simulation results indicate that the QoS-aware cooperative scheme can significantly improve the system performance in terms of throughput and energy efficiency by avoiding negative effect of unconditional cooperation.

Resource Allocation for Uplink CSI Sensing Report in Multi-User WLAN Sensing

Sensing in wireless local area network(WLAN) gains great interests recently. In this paper we focus on the multi-user WLAN sensing problem under the existing 802.11 standards. Multiple stations perform sensing with the access point and transmit channel state information(CSI)report simultaneously on the basis of uplink-orthogonal frequency division multiple access(OFDMA). Considering the transmission resource consumed in CSI report and the padding wastage in OFDMA based CSI report, we optimize the CSI simplification and uplink resource unit(RU)allocation jointly, aiming to balance the sensing accuracy and padding wastage performances in WLAN sensing. We propose the minimize padding maximize efficiency(MPME) algorithm to solve the problem and evaluate the performance of the proposed algorithm through extensive simulations.

Improved MIMO-OFDM scheme for the next generation WLAN

The research and application of wireless local area networks （WLAN） technology are in a stage of rapid development. It has been one of research focuses of the wireless communications field. Through the use of enhanced single-user （SU）/multi-user （MU） multiple input multiple output （MIMO）-orthogonal frequency division multiplexing （OFDM） technology, the next generation WLAN IEEE 802.1 lac dramatically increases the throughput. An improved MIMO-OFDM scheme based on modulation diversity is proposed for the next generation WLAN. It uses two-dimensional modulation diversity to the current IEEE 802.11ac transmission scheme. Through the space-time-frequency component inter- leaver and the rotational modulation, the proposed scheme ex- hibits high spectral efficiency and low error rate in fading channels. The simulation results show that the proposed scheme significantly outperforms the SU/MU MIMO-OFDM scheme in the current IEEE 802.11 ac standard, which is up to 5 dB.

Scheme of Rogue AP detection in managed WLAN based on AP's location

A scheme of rogue access point(Rogue AP)detection based on AP's localization is proposed.Global position system(GPS)information and received signal strength(RSS)information are used to get the location of AP in a smartphone,which is compared with the database located in a remote server.The proposed scheme can detect not only fake access point(Fake AP)but also Evil Twin AP.It can be a user-oriented solution to detecting Rogue AP threats,and users can use it flexibly.

Security analysis of newly ameliorated WAPI protocol

Based on thorough researches on the Chinese wireless local area network （WLAN） security standard, i. e., WLAN authentication and privacy infrastructure （WAPI）, the security of the authentication access process is analyzed with the CK （Canetti-Krawczyk） model and the BAN （Burrows-Abadi- Needham） logic. Results show that it can achieve the alleged authentication and key negotiation goals. Besides those alleged, further analyses indicate that the authentication access process can satisfy other security requirements, such as mutual identity authentication, mutual key control, key confirmation, message integrity check, etc. If the used elliptic curve encryption algorithm and the hash algorithm are secure enough, the protocol can efficiently realize mutual authentication between STAs （station） and APs （access point）. Therefore, WAPI can be applied to replace the security mechanism used in the original WLAN international standard to enhance its security.

MODIFIED ULTRA WIDEBAND CIRCULAR PRINTED MONOPOLE ANTENNA

A simple and compact microstrip-fed ultra wideband （UWB） printed monopole antenna is presented. The antenna is composed of a circular radiator and a finitely grounded plane. The antenna occupies about 16.62 GHz absolute bandwidth and 142.7% relative bandwidth covering from 3.38 GHz to 20 GHz with voltage standing wave ratio （VSWR） below two. A quasi-omnidirectional and quasi-symmetrical radiation pattern in H plane is obtained in the whole bandwidth. The high performance of the antenna is validated with measured and simulated results given. The antenna can be applied for the system design of UWB wireless communication.

Semi-Supervised Clustering Fingerprint Positioning Algorithm Based on Distance Constraints

With the rapid development of WLAN( Wireless Local Area Network) technology,an important target of indoor positioning systems is to improve the positioning accuracy while reducing the online computation.In this paper,it proposes a novel fingerprint positioning algorithm known as semi-supervised affinity propagation clustering based on distance function constraints. We show that by employing affinity propagation techniques,it is able to use a fractional labeled data to adjust similarity matrix of signal space to cluster reference points with high accuracy. The semi-supervised APC uses a combination of machine learning,clustering analysis and fingerprinting algorithm. By collecting data and testing our algorithm in a realistic indoor WLAN environment,the experimental results indicate that the proposed algorithm can improve positioning accuracy while reduce the online localization computation,as compared with the widely used K nearest neighbor and maximum likelihood estimation algorithms.

A NOVEL INDOOR GEO-LOCATION METHOD USING MIMO ARRAY

In a Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) based Wireless Local Area Network (WLAN) system, both Access Points (APs) and Mobile Termi-nals (MTs) are configured with multiple antennas, to make novel indoor geo-location method possible. In this paper, we presented a novel Least Square Support Vector Machine (LS-SVM) based data fusion algorithm to fuse signal strength measurements for indoor geo-location using only a single AP with MIMO arrays. We evaluate our proposed algorithms under indoor environments by MATLAB simulations. Simulation results show that our MIMO-based algorithm is superior to conventional least square algorithm.

Mathematical Analysis of Energy Efficiency in IEEE 802.11 DCF

The standardized IEEE ,802. II distributed coordination function （ DCF） provides a contention-based distributed channel access mechanism for mobile stations to share the wireless medium. However, when stations are mobile or portable units, power consumption becomes a primary issue since terminals are usually battery driven. This paper proposes an analytical model that calculates the energy efficiency of both the basic and the RTS/CTS access mechanisms of the IEEE 802. II protocol. The model is validated with simulation results using NS-2 simulation package. The effects of the network size, the average packet length, the initial contention window and maximum backoff stages on the energy efficiency of both access mechanisms are also investigated. Results show that the basic scheme has low energy efficiency at large packet length and large network size, and depends strongly on the number of stations and the backoff procedure parameters. Conversely, the RTS/CTS mechanism provides higher energy efficiency when the network size is large, and is more robust to variations in the backoff procedure parameters.